Chunking up speech in real time: linguistic predictors and cognitive constraints

Vetchinnikova, Svetlana; Konina, Alena; Williams, Nitin; Mikušová, Nina; Mauranen, Anna

doi:10.1017/langcog.2023.8

Cited by 3 publications

(1 citation statement)

References 91 publications

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“…For language, a proposed window of 6 words 7 translates to 2.4 s when assuming a rate of 150 words per minute 8 . Likewise, the duration of single utterances in speech approaches a median of 2.6 s 9 (see also 10 ).…”

Section: Introductionmentioning

confidence: 99%

Periodic fluctuations in reading times reflect multi-word-chunking

Lo,

Anderson,

Henke

et al. 2023

Sci Rep

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Memory is fleeting. To avoid information loss, humans need to recode verbal stimuli into chunks of limited duration, each containing multiple words. Chunk duration may also be limited neurally by the wavelength of periodic brain activity, so-called neural oscillations. While both cognitive and neural constraints predict some degree of behavioral regularity in processing, this remains to be shown. Our analysis of self-paced reading data from 181 participants reveals periodic patterns at a frequency of $$\sim$$ ∼ 2 Hz. We defined multi-word chunks by using a computational formalization based on dependency annotations and part-of-speech tags. Potential chunk outputs were first generated from the computational formalization and the final chunk outputs were selected based on normalized pointwise mutual information. We show that behavioral periodicity is time-aligned to multi-word chunks, suggesting that the multi-word chunks generated from local dependency clusters may minimize memory demands. This is the first evidence that sentence processing behavior is periodic, consistent with a role of both memory constraints and endogenous electrophysiological rhythms in the formation of chunks during language comprehension.

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Section: Introductionmentioning

confidence: 99%

Periodic fluctuations in reading times reflect multi-word-chunking

Lo,

Anderson,

Henke

et al. 2023

Sci Rep

View full text Add to dashboard Cite

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Exploring the Grammatical Complexity of International Teaching Assistants: A Comparative Corpus Study

Chang,

Raeisi‐Vanani

2024

TESOL Quarterly

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The purpose of this study is to analyze the grammatical complexity features of international teaching assistants' (ITAs) mock‐teaching presentations and to compare the distributions of these features to those found in the Oral English Proficiency Test (a local ITA assessment), university classroom teaching, conversation, and academic writing. The data consisted of 186 prospective ITAs' mock‐teaching presentations collected from two ITA training courses at a large U.S. university: one higher‐level course and one lower‐level course. All presentations were transcribed, proofread, and built into a corpus consisting of 247,043 words. Based on the previous corpus studies, a total of 22 grammatical complexity features were selected for the analysis. Overall, the discourse of ITA mock‐teaching involved a substantial number of both the grammatical complexity features commonly found in spoken conversation (e.g., finite adverbial clauses and modals) and those commonly used in academic writing (e.g., noun premodifiers and prepositional phrases). The frequency distributions of the features differed in complex ways between ITA mock‐teaching and the other registers, as well as between the higher‐level and lower‐level ITAs. Pedagogical implications for ITA training and assessment, and future research directions are discussed at the end.

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Chunk Duration Limits the Learning of Multiword Chunks: Behavioral and Electroencephalography Evidence from Statistical Learning

Henke,

Meyer

2025

Journal of Cognitive Neuroscience

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Language comprehension involves the grouping of words into larger multiword chunks. This is required to recode information into sparser representations to mitigate memory limitations and counteract forgetting. It has been suggested that electrophysiological processing time windows constrain the formation of these units. Specifically, the period of rhythmic neural activity (i.e., slow-frequency neural oscillations) may set an upper limit of 2–3 sec. Here, we assess whether learning of new multiword chunks is also affected by this neural limit. We applied an auditory statistical learning paradigm of an artificial language while manipulating the duration of to-be-learnt chunks. Participants listened to isochronous sequences of disyllabic pseudowords from which they could learn hidden three-word chunks based on transitional probabilities. We presented chunks of 1.95, 2.55, and 3.15 sec that were created by varying the pause interval between pseudowords. In a first behavioral experiment, we tested learning using an implicit target detection task. We found better learning for chunks of 2.55 sec as compared to longer durations in line with an upper limit of the proposed time constraint. In a second experiment, we recorded participants' electroencephalogram during the exposure phase to use frequency tagging as a neural index of statistical learning. Extending the behavioral findings, results show a significant decline in neural tracking for chunks exceeding 3 sec as compared to both shorter durations. Overall, we suggest that language learning is constrained by endogenous time constraints, possibly reflecting electrophysiological processing windows.

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Chunking up speech in real time: linguistic predictors and cognitive constraints

Cited by 3 publications

References 91 publications

Periodic fluctuations in reading times reflect multi-word-chunking

Periodic fluctuations in reading times reflect multi-word-chunking

Exploring the Grammatical Complexity of International Teaching Assistants: A Comparative Corpus Study

Chunk Duration Limits the Learning of Multiword Chunks: Behavioral and Electroencephalography Evidence from Statistical Learning

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